Text Classification
Transformers
PyTorch
Arabic
bert
sentiment-analysis
arabic
marbert
twitter
text-embeddings-inference
Instructions to use iMeshal/arabic-sentiment-classifier-marbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iMeshal/arabic-sentiment-classifier-marbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="iMeshal/arabic-sentiment-classifier-marbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("iMeshal/arabic-sentiment-classifier-marbert") model = AutoModelForSequenceClassification.from_pretrained("iMeshal/arabic-sentiment-classifier-marbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from iMeshal/arabic-sentiment-classifier-marbert: direct link, hf CLI and curl.
- Browser
- Download file 2.69 MB
-
https://huggingface.co/iMeshal/arabic-sentiment-classifier-marbert/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://iMeshal/arabic-sentiment-classifier-marbert@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/iMeshal/arabic-sentiment-classifier-marbert/resolve/refs%2Fpr%2F2/tokenizer.json
2.69 MB
File too large to display, you can check the raw version instead.